andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1876 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: Paul Alper writes: Unless I missed it, you haven’t commented on the recent article of Michael Bang Peterson [with Daniel Sznycer, Aaron Sell, Leda Cosmides, and John Tooby]. It seems to have been reviewed extensively in the lay press. A typical example is here . This review begins with “If you are physically strong, social science scholars believe they can predict whether or not you are more conservative than other men…Men’s upper-body strength predicts their political opinions on economic redistribution, they write, and they believe that the link may reflect psychological traits that evolved in response to our early ancestral environments and continue to influence behavior today. . . . they surveyed hundreds of people in America, Denmark and Argentina about bicep size, socioeconomic status, and support for economic redistribution.” Further, “Despite the fact that the United States, Denmark and Argentina have very different welfare systems, we still see that — at the psychol
sentIndex sentText sentNum sentScore
1 they surveyed hundreds of people in America, Denmark and Argentina about bicep size, socioeconomic status, and support for economic redistribution. [sent-8, score-0.343]
2 ” Further, “Despite the fact that the United States, Denmark and Argentina have very different welfare systems, we still see that — at the psychological level — individuals reason about welfare redistribution in the same way,” says Petersen. [sent-9, score-0.602]
3 “In all three countries, physically strong males consistently pursue the self-interested position on redistribution. [sent-10, score-0.503]
4 and Argentina, the study relied on college students measuring college students’ biceps while in Denmark “a protocol was devised and presented to the subjects over the internet instructing them on how to measure their biceps correctly. [sent-18, score-0.859]
5 To be more specific, they claim that physically strong low-SES 21-year-old men are more likely to favor income redistribution, compared to physically weak low-SES 21-year-old men. [sent-26, score-0.749]
6 From the supplementary material: The interaction effect is not significant when the scale from the Danish study are used to gauge the US subjects’ support for redistribution. [sent-38, score-0.267]
7 The scale measuring support for redistribution in the Argentina sample has a low α-level and, hence, is affected by a high level of random noise. [sent-46, score-0.369]
8 My first reaction when seeing a analysis of young men’s biceps size is that this could be a proxy for age. [sent-57, score-0.512]
9 And, indeed, for the analyses from the two countries where the samples were college students, when age is thrown into the model, the coefficient for biceps size (or, as the authors put it, “upper-body strength”) goes away. [sent-58, score-0.782]
10 The key coefficient is the interaction between biceps size and socioeconomic status. [sent-60, score-0.601]
11 For example, Figure 1 could easily have included points showing average support for income redistribution for respondents broken into bins characterized by SES and biceps size. [sent-68, score-0.714]
12 Such a graph would still have be problem of being contaminated by correlation between age and biceps size, but at least it would show the basic patterns in the data. [sent-71, score-0.286]
13 What they actually found were some correlations among three samples, two of which were of college students. [sent-74, score-0.305]
14 But their abstract says nothing about college students, instead presenting their claims entirely generally, referring only to “men,” never to “young men” or “students. [sent-75, score-0.262]
15 The abstract is clean here (the use the term “predicted” rather than “caused”) but later on they unambiguously write, “Does upper-body strength influence support for economic redistribution in men? [sent-77, score-0.747]
16 Later they write, “Does upper-body strength influence support for economic redistribution in women? [sent-81, score-0.649]
17 Then they go deep into story time: “the results indicate that physically stronger males (rich and poor) are more prone to bargain in their own self-interest . [sent-84, score-0.465]
18 ” And, from the conclusion of the paper, here are all the overstatements at once: We showed that upper-body strength in modern adult men influences their willingness to bargain in their own self-interest over income and wealth redistribution. [sent-88, score-0.563]
19 Actually, I didn’t see anything in the data about bargaining, nor are the causal claims supported by the analysis, and nor do college students represent “modern adult men. [sent-91, score-0.327]
20 and Argentina samples were students, but the authors managed to get through the abstract, intro, and conclusion without mentioning this restriction. [sent-94, score-0.273]
wordName wordTfidf (topN-words)
[('biceps', 0.286), ('redistribution', 0.277), ('physically', 0.249), ('men', 0.189), ('argentina', 0.185), ('strength', 0.161), ('ses', 0.138), ('males', 0.126), ('petersen', 0.116), ('interaction', 0.114), ('items', 0.111), ('denmark', 0.111), ('samples', 0.106), ('authors', 0.106), ('college', 0.103), ('socioeconomic', 0.101), ('psychological', 0.1), ('size', 0.1), ('abstract', 0.098), ('support', 0.092), ('bargain', 0.09), ('bicep', 0.09), ('danish', 0.09), ('welfare', 0.083), ('causal', 0.082), ('students', 0.081), ('countries', 0.081), ('hence', 0.079), ('peterson', 0.074), ('article', 0.072), ('among', 0.07), ('representativeness', 0.069), ('alper', 0.067), ('young', 0.067), ('claimed', 0.066), ('three', 0.066), ('correlations', 0.066), ('unreliable', 0.064), ('holes', 0.064), ('strong', 0.062), ('modern', 0.062), ('conclusion', 0.061), ('claims', 0.061), ('effect', 0.061), ('economic', 0.06), ('could', 0.059), ('influence', 0.059), ('attitudes', 0.059), ('taking', 0.059), ('individuals', 0.059)]
simIndex simValue blogId blogTitle
same-blog 1 1.0000001 1876 andrew gelman stats-2013-05-29-Another one of those “Psychological Science” papers (this time on biceps size and political attitudes among college students)
Introduction: Paul Alper writes: Unless I missed it, you haven’t commented on the recent article of Michael Bang Peterson [with Daniel Sznycer, Aaron Sell, Leda Cosmides, and John Tooby]. It seems to have been reviewed extensively in the lay press. A typical example is here . This review begins with “If you are physically strong, social science scholars believe they can predict whether or not you are more conservative than other men…Men’s upper-body strength predicts their political opinions on economic redistribution, they write, and they believe that the link may reflect psychological traits that evolved in response to our early ancestral environments and continue to influence behavior today. . . . they surveyed hundreds of people in America, Denmark and Argentina about bicep size, socioeconomic status, and support for economic redistribution.” Further, “Despite the fact that the United States, Denmark and Argentina have very different welfare systems, we still see that — at the psychol
2 0.19034226 1878 andrew gelman stats-2013-05-31-How to fix the tabloids? Toward replicable social science research
Introduction: This seems to be the topic of the week. Yesterday I posted on the sister blog some further thoughts on those “Psychological Science” papers on menstrual cycles, biceps size, and political attitudes, tied to a horrible press release from the journal Psychological Science hyping the biceps and politics study. Then I was pointed to these suggestions from Richard Lucas and M. Brent Donnellan have on improving the replicability and reproducibility of research published in the Journal of Research in Personality: It goes without saying that editors of scientific journals strive to publish research that is not only theoretically interesting but also methodologically rigorous. The goal is to select papers that advance the field. Accordingly, editors want to publish findings that can be reproduced and replicated by other scientists. Unfortunately, there has been a recent “crisis in confidence” among psychologists about the quality of psychological research (Pashler & Wagenmakers, 2012)
Introduction: In my article about implausible p-values in psychology studies, I wrote: “Women Are More Likely to Wear Red or Pink at Peak Fertility,” by Alec Beall and Jessica Tracy, is based on two samples: a self-selected sample of 100 women from the Internet, and 24 undergraduates at the University of British Columbia. . . . [There is a problem with] representativeness. What color clothing you wear has a lot to do with where you live and who you hang out with. Participants in an Internet survey and University of British Columbia students aren’t particularly representative of much more than … participants in an Internet survey and University of British Columbia students. In response, I received this in an email from a prominent psychology researcher (not someone I know personally): Complaining that subjects in an experiment were not randomly sampled is what freshmen do before they take their first psychology class. I really *hope* you why that is an absurd criticism – especially of au
4 0.16057122 1860 andrew gelman stats-2013-05-17-How can statisticians help psychologists do their research better?
Introduction: I received two emails yesterday on related topics. First, Stephen Olivier pointed me to this post by Daniel Lakens, who wrote the following open call to statisticians: You would think that if you are passionate about statistics, then you want to help people to calculate them correctly in any way you can. . . . you’d think some statisticians would be interested in helping a poor mathematically challenged psychologist out by offering some practical advice. I’m the right person to ask this question, since I actually have written a lot of material that helps psychologists (and others) with their data analysis. But there clearly are communication difficulties, in that my work and that of other statisticians hasn’t reached Lakens. Sometimes the contributions of statisticians are made indirectly. For example, I wrote Bayesian Data Analysis, and then Kruschke wrote Doing Bayesian Data Analysis. Our statistics book made it possible for Kruschke to write his excellent book for psycholo
5 0.1600405 2236 andrew gelman stats-2014-03-07-Selection bias in the reporting of shaky research
Introduction: I’ll reorder this week’s posts a bit in order to continue on a topic that came up yesterday. A couple days ago a reporter wrote to me asking what I thought of this paper on Money, Status, and the Ovulatory Cycle. I responded: Given the quality of the earlier paper by these researchers, I’m not inclined to believe anything these people write. But, to be specific, I can point out some things: - The authors define low fertility as days 8-14. Oddly enough, these authors in their earlier paper used days 7-14. But according to womenshealth.gov, the most fertile days are between days 10 and 17. The choice of these days affects their analysis, and it is not a good sign that they use different days in different papers. (see more on this point in sections 2.3 and 3.1 of this paper: http://www.stat.columbia.edu/~gelman/research/unpublished/p_hacking.pdf) - They perform a lot of different analyses, and many others could be performed. For example, “Study 1 indicates that ovul
7 0.1503755 1114 andrew gelman stats-2012-01-12-Controversy about average personality differences between men and women
8 0.14094186 888 andrew gelman stats-2011-09-03-A psychology researcher asks: Is Anova dead?
10 0.13521442 1139 andrew gelman stats-2012-01-26-Suggested resolution of the Bem paradox
11 0.13413119 797 andrew gelman stats-2011-07-11-How do we evaluate a new and wacky claim?
12 0.13343792 2255 andrew gelman stats-2014-03-19-How Americans vote
13 0.13304658 2006 andrew gelman stats-2013-09-03-Evaluating evidence from published research
16 0.12774232 1910 andrew gelman stats-2013-06-22-Struggles over the criticism of the “cannabis users and IQ change” paper
17 0.12735894 2245 andrew gelman stats-2014-03-12-More on publishing in journals
18 0.12625504 1 andrew gelman stats-2010-04-22-Political Belief Networks: Socio-cognitive Heterogeneity in American Public Opinion
topicId topicWeight
[(0, 0.312), (1, -0.063), (2, 0.082), (3, -0.166), (4, -0.015), (5, -0.042), (6, -0.045), (7, 0.003), (8, -0.048), (9, 0.043), (10, -0.011), (11, 0.024), (12, -0.046), (13, 0.019), (14, 0.075), (15, -0.011), (16, 0.021), (17, 0.025), (18, -0.038), (19, -0.003), (20, -0.003), (21, -0.027), (22, -0.032), (23, -0.034), (24, 0.019), (25, 0.036), (26, 0.024), (27, -0.037), (28, 0.001), (29, -0.002), (30, 0.019), (31, 0.002), (32, -0.011), (33, -0.004), (34, 0.005), (35, 0.02), (36, -0.031), (37, -0.024), (38, -0.019), (39, -0.016), (40, -0.01), (41, -0.012), (42, 0.023), (43, 0.006), (44, 0.037), (45, -0.043), (46, -0.005), (47, -0.005), (48, -0.011), (49, -0.005)]
simIndex simValue blogId blogTitle
same-blog 1 0.97490394 1876 andrew gelman stats-2013-05-29-Another one of those “Psychological Science” papers (this time on biceps size and political attitudes among college students)
Introduction: Paul Alper writes: Unless I missed it, you haven’t commented on the recent article of Michael Bang Peterson [with Daniel Sznycer, Aaron Sell, Leda Cosmides, and John Tooby]. It seems to have been reviewed extensively in the lay press. A typical example is here . This review begins with “If you are physically strong, social science scholars believe they can predict whether or not you are more conservative than other men…Men’s upper-body strength predicts their political opinions on economic redistribution, they write, and they believe that the link may reflect psychological traits that evolved in response to our early ancestral environments and continue to influence behavior today. . . . they surveyed hundreds of people in America, Denmark and Argentina about bicep size, socioeconomic status, and support for economic redistribution.” Further, “Despite the fact that the United States, Denmark and Argentina have very different welfare systems, we still see that — at the psychol
Introduction: Etienne LeBel writes: You’ve probably already seen it, but I thought you could have a lot of fun with this one!! The article , with the admirably clear title given above, is by James McNulty, Michael Olson, Andrea Meltzer, Matthew Shaffer, and begins as follows: For decades, social psychological theories have posited that the automatic processes captured by implicit measures have implications for social outcomes. Yet few studies have demonstrated any long-term implications of automatic processes, and some scholars have begun to question the relevance and even the validity of these theories. At baseline of our longitudinal study, 135 newlywed couples (270 individuals) completed an explicit measure of their conscious attitudes toward their relationship and an implicit measure of their automatic attitudes toward their partner. They then reported their marital satisfaction every 6 months for the next 4 years. We found no correlation between spouses’ automatic and conscious attitu
3 0.86816114 1114 andrew gelman stats-2012-01-12-Controversy about average personality differences between men and women
Introduction: Blogger Echidne pointed me to a recent article , “The Distance Between Mars and Venus: Measuring Global Sex Differences in Personality,” by Marco Del Giudice, Tom Booth, and Paul Irwing, who find: Sex differences in personality are believed to be comparatively small. However, research in this area has suffered from significant methodological limitations. We advance a set of guidelines for overcoming those limitations: (a) measure personality with a higher resolution than that afforded by the Big Five; (b) estimate sex differences on latent factors; and (c) assess global sex differences with multivariate effect sizes. . . . We found a global effect size D = 2.71, corresponding to an overlap of only 10% between the male and female distributions. Even excluding the factor showing the largest univariate ES [effect size], the global effect size was D = 1.71 (24% overlap). Echidne quotes a news article in which one of the study’s authors going overboard: “Psychologically, men a
4 0.85544801 2220 andrew gelman stats-2014-02-22-Quickies
Introduction: I received a few emails today on bloggable topics. Rather than expanding each response into a full post, I thought I’d just handle them all quickly. 1. Steve Roth asks what I think of this graph : I replied: Interseting but perhaps misleading, as of course any estimate of elasticity of -20 or +5 or whatever is just crap, and so the real question is what is happening in the more reasonable range. 2. One of my General Social Studies colleagues pointed me to this report , writing “FYI – some interesting new results, using the linked GSS-NDI data. I trust this study will raise some heated discussions.” Another colleague wrote, “I’m rather skeptical of the result but at least they spelled GSS right.” The topic is a paper, “Anti-Gay Prejudice and All-Cause Mortality Among Heterosexuals in the United States,” published by Mark Hatzenbuehler, Anna Bellatorre, and Peter Muennig. My reaction: Yes, it seems ludicrous to me. Especially this: The researchers wante
Introduction: Last week I published in Slate a critique of a paper that appeared in the journal Psychological Science. That paper, by Alec Beall and Jessica Tracy, found that women who were at peak fertility were three times more likely to wear red or pink shirts, compared to women at other points in their menstrual cycles. The study was based an 100 participants on the internet and 24 college students. In my critique, I argued that we had no reason to believe the results generalized to the larger population, because (1) the samples were not representative, (2) the measurements were noisy, (3) the researchers did not use the correct dates of peak fertility, and (4) there were many different comparisons that could have been reported in the data, so there was nothing special about a particular comparison being statistically significant. I likened their paper to other work which I considered flawed for multiple comparisons (too many researcher degrees of freedom), including a claimed relation bet
6 0.84722388 1860 andrew gelman stats-2013-05-17-How can statisticians help psychologists do their research better?
7 0.84663141 1226 andrew gelman stats-2012-03-22-Story time meets the all-else-equal fallacy and the fallacy of measurement
9 0.84099478 177 andrew gelman stats-2010-08-02-Reintegrating rebels into civilian life: Quasi-experimental evidence from Burundi
10 0.84095913 1910 andrew gelman stats-2013-06-22-Struggles over the criticism of the “cannabis users and IQ change” paper
11 0.83724219 2236 andrew gelman stats-2014-03-07-Selection bias in the reporting of shaky research
12 0.83380216 1128 andrew gelman stats-2012-01-19-Sharon Begley: Worse than Stephen Jay Gould?
13 0.83267522 2336 andrew gelman stats-2014-05-16-How much can we learn about individual-level causal claims from state-level correlations?
15 0.82009155 98 andrew gelman stats-2010-06-19-Further thoughts on happiness and life satisfaction research
16 0.81733549 2223 andrew gelman stats-2014-02-24-“Edlin’s rule” for routinely scaling down published estimates
17 0.80454785 706 andrew gelman stats-2011-05-11-The happiness gene: My bottom line (for now)
18 0.79939806 382 andrew gelman stats-2010-10-30-“Presidential Election Outcomes Directly Influence Suicide Rates”
19 0.79688662 2241 andrew gelman stats-2014-03-10-Preregistration: what’s in it for you?
topicId topicWeight
[(13, 0.021), (15, 0.052), (16, 0.087), (21, 0.028), (24, 0.141), (45, 0.011), (47, 0.017), (55, 0.014), (57, 0.118), (86, 0.024), (95, 0.018), (98, 0.025), (99, 0.292)]
simIndex simValue blogId blogTitle
1 0.97569919 1460 andrew gelman stats-2012-08-16-“Real data can be a pain”
Introduction: Michael McLaughlin sent me the following query with the above title. Some time ago, I [McLaughlin] was handed a dataset that needed to be modeled. It was generated as follows: 1. Random navigation errors, historically a binary mixture of normal and Laplace with a common mean, were collected by observation. 2. Sadly, these data were recorded with too few decimal places so that the resulting quantization is clearly visible in a scatterplot. 3. The quantized data were then interpolated (to an unobserved location). The final result looks like fuzzy points (small scale jitter) at quantized intervals spanning a much larger scale (the parent mixture distribution). This fuzziness, likely ~normal or ~Laplace, results from the interpolation. Otherwise, the data would look like a discrete analogue of the normal/Laplace mixture. I would like to characterize the latent normal/Laplace mixture distribution but the quantization is “getting in the way”. When I tried MCMC on this proble
Introduction: An experimental psychologist was wondering about the standards in that field for “acceptable reliability” (when looking at inter-rater reliability in coding data). He wondered, for example, if some variation on signal detectability theory might be applied to adjust for inter-rater differences in criteria for saying some code is present. What about Cohen’s kappa? The psychologist wrote: Cohen’s kappa does adjust for “guessing,” but its assumptions are not well motivated, perhaps not any more than adjustments for guessing versus the application of signal detectability theory where that can be applied. But one can’t do a straightforward application of signal detectability theory for reliability in that you don’t know whether the signal is present or not. I think measurement issues are important but I don’t have enough experience in this area to answer the question without knowing more about the problem that this researcher is working on. I’m posting it here because I imagine t
Introduction: Uberbloggers Andrew Sullivan and Matthew Yglesias were kind enough to link to my five-year-old post with graphs from Red State Blue State on time trends of average income by state. Here are the graphs : Yglesias’s take-home point: There isn’t that much change over time in states’ economic well-being. All things considered the best predictor of how rich a state was in 2000 was simply how rich it was in 1929…. Massachusetts and Connecticut have always been rich and Arkansas and Mississippi have always been poor. I’d like to point to a different feature of the graphs, which is that, although the rankings of the states haven’t changed much (as can be seen from the “2000 compared to 1929″ scale), the relative values of the incomes have converged quite a bit—at least, they converged from about 1930 to 1980 before hitting some level of stability. And the rankings have changed a bit. My impression (without checking the numbers) is that New York and Connecticut were
same-blog 4 0.96649432 1876 andrew gelman stats-2013-05-29-Another one of those “Psychological Science” papers (this time on biceps size and political attitudes among college students)
Introduction: Paul Alper writes: Unless I missed it, you haven’t commented on the recent article of Michael Bang Peterson [with Daniel Sznycer, Aaron Sell, Leda Cosmides, and John Tooby]. It seems to have been reviewed extensively in the lay press. A typical example is here . This review begins with “If you are physically strong, social science scholars believe they can predict whether or not you are more conservative than other men…Men’s upper-body strength predicts their political opinions on economic redistribution, they write, and they believe that the link may reflect psychological traits that evolved in response to our early ancestral environments and continue to influence behavior today. . . . they surveyed hundreds of people in America, Denmark and Argentina about bicep size, socioeconomic status, and support for economic redistribution.” Further, “Despite the fact that the United States, Denmark and Argentina have very different welfare systems, we still see that — at the psychol
5 0.9660269 861 andrew gelman stats-2011-08-19-Will Stan work well with 40×40 matrices?
Introduction: Tomas Iesmantas writes: I’m dealing with high dimensional (40-50 parameters) hierarchical bayesian model applied to nonlinear Poisson regression problem. Now I’m using an adaptive version for the Metropolis adjusted Langevin algorithm with a truncated drift (Yves F. Atchade, 2003) to obtain samples from posterior. But this algorithm is not very efficient in my case, it needs several millions iterations as burn-in period. And simulation takes quite a long time, since algorithm has to work with 40×40 matrices. Maybe you know another MCMC algorithm which could take not so many burn-in samples and would be able to deal with nonlinear regression? In non-hierarchical nonlinear regression model adaptive metropolis algorithm is enough, but in hierarchical case I could use something more effective. My reply: Try fitting the model in Stan. If that doesn’t work, let me know.
6 0.96584713 1036 andrew gelman stats-2011-11-30-Stan uses Nuts!
7 0.96394604 1120 andrew gelman stats-2012-01-15-Fun fight over the Grover search algorithm
8 0.96188354 1044 andrew gelman stats-2011-12-06-The K Foundation burns Cosma’s turkey
9 0.95128369 35 andrew gelman stats-2010-05-16-Another update on the spam email study
10 0.95017952 816 andrew gelman stats-2011-07-22-“Information visualization” vs. “Statistical graphics”
11 0.94902849 989 andrew gelman stats-2011-11-03-This post does not mention Wegman
12 0.94863665 1870 andrew gelman stats-2013-05-26-How to understand coefficients that reverse sign when you start controlling for things?
13 0.9458251 1108 andrew gelman stats-2012-01-09-Blogging, polemical and otherwise
14 0.94155896 306 andrew gelman stats-2010-09-29-Statistics and the end of time
15 0.94150037 215 andrew gelman stats-2010-08-18-DataMarket
16 0.94061577 902 andrew gelman stats-2011-09-12-The importance of style in academic writing
17 0.93938214 2137 andrew gelman stats-2013-12-17-Replication backlash
18 0.93695581 1018 andrew gelman stats-2011-11-19-Tempering and modes
19 0.93671227 2318 andrew gelman stats-2014-05-04-Stan (& JAGS) Tutorial on Linear Mixed Models